
<!DOCTYPE html>

<html lang="zh">
  <head>
    <meta charset="utf-8" />
    <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />

    <title>6.6 使用argparse进行调参 &#8212; 深入浅出PyTorch</title>
    
  <!-- Loaded before other Sphinx assets -->
  <link href="../_static/styles/theme.css?digest=1999514e3f237ded88cf" rel="stylesheet">
<link href="../_static/styles/pydata-sphinx-theme.css?digest=1999514e3f237ded88cf" rel="stylesheet">

    
  <link rel="stylesheet"
    href="../_static/vendor/fontawesome/5.13.0/css/all.min.css">
  <link rel="preload" as="font" type="font/woff2" crossorigin
    href="../_static/vendor/fontawesome/5.13.0/webfonts/fa-solid-900.woff2">
  <link rel="preload" as="font" type="font/woff2" crossorigin
    href="../_static/vendor/fontawesome/5.13.0/webfonts/fa-brands-400.woff2">

    <link rel="stylesheet" type="text/css" href="../_static/pygments.css" />
    <link rel="stylesheet" href="../_static/styles/sphinx-book-theme.css?digest=62ba249389abaaa9ffc34bf36a076bdc1d65ee18" type="text/css" />
    <link rel="stylesheet" type="text/css" href="../_static/togglebutton.css" />
    <link rel="stylesheet" type="text/css" href="../_static/mystnb.css" />
    <link rel="stylesheet" type="text/css" href="../_static/plot_directive.css" />
    
  <!-- Pre-loaded scripts that we'll load fully later -->
  <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=1999514e3f237ded88cf">

    <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
    <script src="../_static/jquery.js"></script>
    <script src="../_static/underscore.js"></script>
    <script src="../_static/doctools.js"></script>
    <script>let toggleHintShow = 'Click to show';</script>
    <script>let toggleHintHide = 'Click to hide';</script>
    <script>let toggleOpenOnPrint = 'true';</script>
    <script src="../_static/togglebutton.js"></script>
    <script src="../_static/scripts/sphinx-book-theme.js?digest=f31d14ad54b65d19161ba51d4ffff3a77ae00456"></script>
    <script>var togglebuttonSelector = '.toggle, .admonition.dropdown, .tag_hide_input div.cell_input, .tag_hide-input div.cell_input, .tag_hide_output div.cell_output, .tag_hide-output div.cell_output, .tag_hide_cell.cell, .tag_hide-cell.cell';</script>
    <link rel="index" title="索引" href="../genindex.html" />
    <link rel="search" title="搜索" href="../search.html" />
    <link rel="next" title="PyTorch模型定义与进阶训练技巧" href="PyTorch%E6%A8%A1%E5%9E%8B%E5%AE%9A%E4%B9%89%E4%B8%8E%E8%BF%9B%E9%98%B6%E8%AE%AD%E7%BB%83%E6%8A%80%E5%B7%A7.html" />
    <link rel="prev" title="6.5 数据增强-imgaug" href="6.5%20%E6%95%B0%E6%8D%AE%E5%A2%9E%E5%BC%BA-imgaug.html" />
    <meta name="viewport" content="width=device-width, initial-scale=1" />
    <meta name="docsearch:language" content="zh">
    

    <!-- Google Analytics -->
    
  </head>
  <body data-spy="scroll" data-target="#bd-toc-nav" data-offset="60">
<!-- Checkboxes to toggle the left sidebar -->
<input type="checkbox" class="sidebar-toggle" name="__navigation" id="__navigation" aria-label="Toggle navigation sidebar">
<label class="overlay overlay-navbar" for="__navigation">
    <div class="visually-hidden">Toggle navigation sidebar</div>
</label>
<!-- Checkboxes to toggle the in-page toc -->
<input type="checkbox" class="sidebar-toggle" name="__page-toc" id="__page-toc" aria-label="Toggle in-page Table of Contents">
<label class="overlay overlay-pagetoc" for="__page-toc">
    <div class="visually-hidden">Toggle in-page Table of Contents</div>
</label>
<!-- Headers at the top -->
<div class="announcement header-item noprint"></div>
<div class="header header-item noprint"></div>

    
    <div class="container-fluid" id="banner"></div>

    

    <div class="container-xl">
      <div class="row">
          
<!-- Sidebar -->
<div class="bd-sidebar noprint" id="site-navigation">
    <div class="bd-sidebar__content">
        <div class="bd-sidebar__top"><div class="navbar-brand-box">
    <a class="navbar-brand text-wrap" href="../index.html">
      
      
      
      <h1 class="site-logo" id="site-title">深入浅出PyTorch</h1>
      
    </a>
</div><form class="bd-search d-flex align-items-center" action="../search.html" method="get">
  <i class="icon fas fa-search"></i>
  <input type="search" class="form-control" name="q" id="search-input" placeholder="Search the docs ..." aria-label="Search the docs ..." autocomplete="off" >
</form><nav class="bd-links" id="bd-docs-nav" aria-label="Main">
    <div class="bd-toc-item active">
        <p aria-level="2" class="caption" role="heading">
 <span class="caption-text">
  目录
 </span>
</p>
<ul class="current nav bd-sidenav">
 <li class="toctree-l1 has-children">
  <a class="reference internal" href="../%E7%AC%AC%E4%B8%80%E7%AB%A0/index.html">
   第一章：PyTorch的简介和安装
  </a>
  <input class="toctree-checkbox" id="toctree-checkbox-1" name="toctree-checkbox-1" type="checkbox"/>
  <label for="toctree-checkbox-1">
   <i class="fas fa-chevron-down">
   </i>
  </label>
  <ul>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%B8%80%E7%AB%A0/1.1%20PyTorch%E7%AE%80%E4%BB%8B.html">
     1.1 PyTorch简介
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%B8%80%E7%AB%A0/1.2%20PyTorch%E7%9A%84%E5%AE%89%E8%A3%85.html">
     1.2 PyTorch的安装
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%B8%80%E7%AB%A0/1.3%20PyTorch%E7%9B%B8%E5%85%B3%E8%B5%84%E6%BA%90.html">
     1.3 PyTorch相关资源
    </a>
   </li>
  </ul>
 </li>
 <li class="toctree-l1 has-children">
  <a class="reference internal" href="../%E7%AC%AC%E4%BA%8C%E7%AB%A0/index.html">
   第二章：PyTorch基础知识
  </a>
  <input class="toctree-checkbox" id="toctree-checkbox-2" name="toctree-checkbox-2" type="checkbox"/>
  <label for="toctree-checkbox-2">
   <i class="fas fa-chevron-down">
   </i>
  </label>
  <ul>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%BA%8C%E7%AB%A0/2.1%20%E5%BC%A0%E9%87%8F.html">
     2.1 张量
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%BA%8C%E7%AB%A0/2.2%20%E8%87%AA%E5%8A%A8%E6%B1%82%E5%AF%BC.html">
     2.2 自动求导
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%BA%8C%E7%AB%A0/2.3%20%E5%B9%B6%E8%A1%8C%E8%AE%A1%E7%AE%97%E7%AE%80%E4%BB%8B.html">
     2.3 并行计算简介
    </a>
   </li>
  </ul>
 </li>
 <li class="toctree-l1 has-children">
  <a class="reference internal" href="../%E7%AC%AC%E4%B8%89%E7%AB%A0/index.html">
   第三章：PyTorch的主要组成模块
  </a>
  <input class="toctree-checkbox" id="toctree-checkbox-3" name="toctree-checkbox-3" type="checkbox"/>
  <label for="toctree-checkbox-3">
   <i class="fas fa-chevron-down">
   </i>
  </label>
  <ul>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%B8%89%E7%AB%A0/3.1%20%E6%80%9D%E8%80%83%EF%BC%9A%E5%AE%8C%E6%88%90%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E7%9A%84%E5%BF%85%E8%A6%81%E9%83%A8%E5%88%86.html">
     3.1 思考：完成深度学习的必要部分
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%B8%89%E7%AB%A0/3.2%20%E5%9F%BA%E6%9C%AC%E9%85%8D%E7%BD%AE.html">
     3.2 基本配置
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%B8%89%E7%AB%A0/3.3%20%E6%95%B0%E6%8D%AE%E8%AF%BB%E5%85%A5.html">
     3.3 数据读入
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%B8%89%E7%AB%A0/3.4%20%E6%A8%A1%E5%9E%8B%E6%9E%84%E5%BB%BA.html">
     3.4 模型构建
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%B8%89%E7%AB%A0/3.5%20%E6%A8%A1%E5%9E%8B%E5%88%9D%E5%A7%8B%E5%8C%96.html">
     3.5 模型初始化
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%B8%89%E7%AB%A0/3.6%20%E6%8D%9F%E5%A4%B1%E5%87%BD%E6%95%B0.html">
     3.6 损失函数
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%B8%89%E7%AB%A0/3.7%20%E8%AE%AD%E7%BB%83%E4%B8%8E%E8%AF%84%E4%BC%B0.html">
     3.7 训练和评估
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%B8%89%E7%AB%A0/3.8%20%E5%8F%AF%E8%A7%86%E5%8C%96.html">
     3.8 可视化
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%B8%89%E7%AB%A0/3.9%20%E4%BC%98%E5%8C%96%E5%99%A8.html">
     3.9 Pytorch优化器
    </a>
   </li>
  </ul>
 </li>
 <li class="toctree-l1 has-children">
  <a class="reference internal" href="../%E7%AC%AC%E5%9B%9B%E7%AB%A0/index.html">
   第四章：PyTorch基础实战
  </a>
  <input class="toctree-checkbox" id="toctree-checkbox-4" name="toctree-checkbox-4" type="checkbox"/>
  <label for="toctree-checkbox-4">
   <i class="fas fa-chevron-down">
   </i>
  </label>
  <ul>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E5%9B%9B%E7%AB%A0/%E5%9F%BA%E7%A1%80%E5%AE%9E%E6%88%98%E2%80%94%E2%80%94FashionMNIST%E6%97%B6%E8%A3%85%E5%88%86%E7%B1%BB.html">
     基础实战——FashionMNIST时装分类
    </a>
   </li>
  </ul>
 </li>
 <li class="toctree-l1 has-children">
  <a class="reference internal" href="../%E7%AC%AC%E4%BA%94%E7%AB%A0/index.html">
   第五章：PyTorch模型定义
  </a>
  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
  <label for="toctree-checkbox-5">
   <i class="fas fa-chevron-down">
   </i>
  </label>
  <ul>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%BA%94%E7%AB%A0/5.1%20PyTorch%E6%A8%A1%E5%9E%8B%E5%AE%9A%E4%B9%89%E7%9A%84%E6%96%B9%E5%BC%8F.html">
     5.1 PyTorch模型定义的方式
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%BA%94%E7%AB%A0/5.2%20%E5%88%A9%E7%94%A8%E6%A8%A1%E5%9E%8B%E5%9D%97%E5%BF%AB%E9%80%9F%E6%90%AD%E5%BB%BA%E5%A4%8D%E6%9D%82%E7%BD%91%E7%BB%9C.html">
     5.2 利用模型块快速搭建复杂网络
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%BA%94%E7%AB%A0/5.3%20PyTorch%E4%BF%AE%E6%94%B9%E6%A8%A1%E5%9E%8B.html">
     5.3 PyTorch修改模型
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%BA%94%E7%AB%A0/5.4%20PyTorh%E6%A8%A1%E5%9E%8B%E4%BF%9D%E5%AD%98%E4%B8%8E%E8%AF%BB%E5%8F%96.html">
     5.4 PyTorch模型保存与读取
    </a>
   </li>
  </ul>
 </li>
 <li class="toctree-l1 current active has-children">
  <a class="reference internal" href="index.html">
   第六章：PyTorch进阶训练技巧
  </a>
  <input checked="" class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
  <label for="toctree-checkbox-6">
   <i class="fas fa-chevron-down">
   </i>
  </label>
  <ul class="current">
   <li class="toctree-l2">
    <a class="reference internal" href="6.1%20%E8%87%AA%E5%AE%9A%E4%B9%89%E6%8D%9F%E5%A4%B1%E5%87%BD%E6%95%B0.html">
     6.1 自定义损失函数
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="6.2%20%E5%8A%A8%E6%80%81%E8%B0%83%E6%95%B4%E5%AD%A6%E4%B9%A0%E7%8E%87.html">
     6.2 动态调整学习率
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="6.3%20%E6%A8%A1%E5%9E%8B%E5%BE%AE%E8%B0%83-torchvision.html">
     6.3 模型微调-torchvision
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="6.3%20%E6%A8%A1%E5%9E%8B%E5%BE%AE%E8%B0%83-timm.html">
     6.3 模型微调 - timm
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="6.4%20%E5%8D%8A%E7%B2%BE%E5%BA%A6%E8%AE%AD%E7%BB%83.html">
     6.4 半精度训练
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="6.5%20%E6%95%B0%E6%8D%AE%E5%A2%9E%E5%BC%BA-imgaug.html">
     6.5 数据增强-imgaug
    </a>
   </li>
   <li class="toctree-l2 current active">
    <a class="current reference internal" href="#">
     6.6 使用argparse进行调参
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="PyTorch%E6%A8%A1%E5%9E%8B%E5%AE%9A%E4%B9%89%E4%B8%8E%E8%BF%9B%E9%98%B6%E8%AE%AD%E7%BB%83%E6%8A%80%E5%B7%A7.html">
     PyTorch模型定义与进阶训练技巧
    </a>
   </li>
  </ul>
 </li>
 <li class="toctree-l1 has-children">
  <a class="reference internal" href="../%E7%AC%AC%E4%B8%83%E7%AB%A0/index.html">
   第七章：PyTorch可视化
  </a>
  <input class="toctree-checkbox" id="toctree-checkbox-7" name="toctree-checkbox-7" type="checkbox"/>
  <label for="toctree-checkbox-7">
   <i class="fas fa-chevron-down">
   </i>
  </label>
  <ul>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%B8%83%E7%AB%A0/7.1%20%E5%8F%AF%E8%A7%86%E5%8C%96%E7%BD%91%E7%BB%9C%E7%BB%93%E6%9E%84.html">
     7.1 可视化网络结构
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%B8%83%E7%AB%A0/7.2%20CNN%E5%8D%B7%E7%A7%AF%E5%B1%82%E5%8F%AF%E8%A7%86%E5%8C%96.html">
     7.2 CNN可视化
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E4%B8%83%E7%AB%A0/7.3%20%E4%BD%BF%E7%94%A8TensorBoard%E5%8F%AF%E8%A7%86%E5%8C%96%E8%AE%AD%E7%BB%83%E8%BF%87%E7%A8%8B.html">
     7.3 使用TensorBoard可视化训练过程
    </a>
   </li>
  </ul>
 </li>
 <li class="toctree-l1 has-children">
  <a class="reference internal" href="../%E7%AC%AC%E5%85%AB%E7%AB%A0/index.html">
   第八章：PyTorch生态简介
  </a>
  <input class="toctree-checkbox" id="toctree-checkbox-8" name="toctree-checkbox-8" type="checkbox"/>
  <label for="toctree-checkbox-8">
   <i class="fas fa-chevron-down">
   </i>
  </label>
  <ul>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E5%85%AB%E7%AB%A0/8.1%20%E6%9C%AC%E7%AB%A0%E7%AE%80%E4%BB%8B.html">
     8.1 本章简介
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E5%85%AB%E7%AB%A0/8.2%20%E5%9B%BE%E5%83%8F%20-%20torchvision.html">
     8.2 torchvision
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E5%85%AB%E7%AB%A0/8.3%20%E8%A7%86%E9%A2%91%20-%20PyTorchVideo.html">
     8.3 PyTorchVideo简介
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E5%85%AB%E7%AB%A0/8.4%20%E6%96%87%E6%9C%AC%20-%20torchtext.html">
     8.4 torchtext简介
    </a>
   </li>
   <li class="toctree-l2">
    <a class="reference internal" href="../%E7%AC%AC%E5%85%AB%E7%AB%A0/transforms%E5%AE%9E%E6%93%8D.html">
     transforms实战
    </a>
   </li>
  </ul>
 </li>
</ul>

    </div>
</nav></div>
        <div class="bd-sidebar__bottom">
             <!-- To handle the deprecated key -->
            
            <div class="navbar_extra_footer">
            Theme by the <a href="https://ebp.jupyterbook.org">Executable Book Project</a>
            </div>
            
        </div>
    </div>
    <div id="rtd-footer-container"></div>
</div>


          


          
<!-- A tiny helper pixel to detect if we've scrolled -->
<div class="sbt-scroll-pixel-helper"></div>
<!-- Main content -->
<div class="col py-0 content-container">
    
    <div class="header-article row sticky-top noprint">
        



<div class="col py-1 d-flex header-article-main">
    <div class="header-article__left">
        
        <label for="__navigation"
  class="headerbtn"
  data-toggle="tooltip"
data-placement="right"
title="Toggle navigation"
>
  

<span class="headerbtn__icon-container">
  <i class="fas fa-bars"></i>
  </span>

</label>

        
    </div>
    <div class="header-article__right">
<button onclick="toggleFullScreen()"
  class="headerbtn"
  data-toggle="tooltip"
data-placement="bottom"
title="Fullscreen mode"
>
  

<span class="headerbtn__icon-container">
  <i class="fas fa-expand"></i>
  </span>

</button>

<div class="menu-dropdown menu-dropdown-repository-buttons">
  <button class="headerbtn menu-dropdown__trigger"
      aria-label="Source repositories">
      <i class="fab fa-github"></i>
  </button>
  <div class="menu-dropdown__content">
    <ul>
      <li>
        <a href="https://github.com/datawhalechina/thorough-pytorch"
   class="headerbtn"
   data-toggle="tooltip"
data-placement="left"
title="Source repository"
>
  

<span class="headerbtn__icon-container">
  <i class="fab fa-github"></i>
  </span>
<span class="headerbtn__text-container">repository</span>
</a>

      </li>
      
      <li>
        <a href="https://github.com/datawhalechina/thorough-pytorch/issues/new?title=Issue%20on%20page%20%2F第六章/6.6 使用argparse进行调参.html&body=Your%20issue%20content%20here."
   class="headerbtn"
   data-toggle="tooltip"
data-placement="left"
title="Open an issue"
>
  

<span class="headerbtn__icon-container">
  <i class="fas fa-lightbulb"></i>
  </span>
<span class="headerbtn__text-container">open issue</span>
</a>

      </li>
      
      <li>
        <a href="https://github.com/datawhalechina/thorough-pytorch/edit/master/第六章/6.6 使用argparse进行调参.md"
   class="headerbtn"
   data-toggle="tooltip"
data-placement="left"
title="Edit this page"
>
  

<span class="headerbtn__icon-container">
  <i class="fas fa-pencil-alt"></i>
  </span>
<span class="headerbtn__text-container">suggest edit</span>
</a>

      </li>
      
    </ul>
  </div>
</div>

<div class="menu-dropdown menu-dropdown-download-buttons">
  <button class="headerbtn menu-dropdown__trigger"
      aria-label="Download this page">
      <i class="fas fa-download"></i>
  </button>
  <div class="menu-dropdown__content">
    <ul>
      <li>
        <a href="../_sources/第六章/6.6 使用argparse进行调参.md.txt"
   class="headerbtn"
   data-toggle="tooltip"
data-placement="left"
title="Download source file"
>
  

<span class="headerbtn__icon-container">
  <i class="fas fa-file"></i>
  </span>
<span class="headerbtn__text-container">.md</span>
</a>

      </li>
      
      <li>
        
<button onclick="printPdf(this)"
  class="headerbtn"
  data-toggle="tooltip"
data-placement="left"
title="Print to PDF"
>
  

<span class="headerbtn__icon-container">
  <i class="fas fa-file-pdf"></i>
  </span>
<span class="headerbtn__text-container">.pdf</span>
</button>

      </li>
      
    </ul>
  </div>
</div>
<label for="__page-toc"
  class="headerbtn headerbtn-page-toc"
  
>
  

<span class="headerbtn__icon-container">
  <i class="fas fa-list"></i>
  </span>

</label>

    </div>
</div>

<!-- Table of contents -->
<div class="col-md-3 bd-toc show noprint">
    <div class="tocsection onthispage pt-5 pb-3">
        <i class="fas fa-list"></i> Contents
    </div>
    <nav id="bd-toc-nav" aria-label="Page">
        <ul class="visible nav section-nav flex-column">
 <li class="toc-h2 nav-item toc-entry">
  <a class="reference internal nav-link" href="#id1">
   引言
  </a>
 </li>
 <li class="toc-h2 nav-item toc-entry">
  <a class="reference internal nav-link" href="#id2">
   6.6.1 argparse简介
  </a>
 </li>
 <li class="toc-h2 nav-item toc-entry">
  <a class="reference internal nav-link" href="#id3">
   6.6.2 argparse的使用
  </a>
 </li>
 <li class="toc-h2 nav-item toc-entry">
  <a class="reference internal nav-link" href="#id4">
   6.6.3 更加高效使用argparse修改超参数
  </a>
 </li>
 <li class="toc-h2 nav-item toc-entry">
  <a class="reference internal nav-link" href="#id5">
   总结
  </a>
 </li>
</ul>

    </nav>
</div>
    </div>
    <div class="article row">
        <div class="col pl-md-3 pl-lg-5 content-container">
            <!-- Table of contents that is only displayed when printing the page -->
            <div id="jb-print-docs-body" class="onlyprint">
                <h1>6.6 使用argparse进行调参</h1>
                <!-- Table of contents -->
                <div id="print-main-content">
                    <div id="jb-print-toc">
                        
                        <div>
                            <h2> Contents </h2>
                        </div>
                        <nav aria-label="Page">
                            <ul class="visible nav section-nav flex-column">
 <li class="toc-h2 nav-item toc-entry">
  <a class="reference internal nav-link" href="#id1">
   引言
  </a>
 </li>
 <li class="toc-h2 nav-item toc-entry">
  <a class="reference internal nav-link" href="#id2">
   6.6.1 argparse简介
  </a>
 </li>
 <li class="toc-h2 nav-item toc-entry">
  <a class="reference internal nav-link" href="#id3">
   6.6.2 argparse的使用
  </a>
 </li>
 <li class="toc-h2 nav-item toc-entry">
  <a class="reference internal nav-link" href="#id4">
   6.6.3 更加高效使用argparse修改超参数
  </a>
 </li>
 <li class="toc-h2 nav-item toc-entry">
  <a class="reference internal nav-link" href="#id5">
   总结
  </a>
 </li>
</ul>

                        </nav>
                    </div>
                </div>
            </div>
            <main id="main-content" role="main">
                
              <div>
                
  <section class="tex2jax_ignore mathjax_ignore" id="argparse">
<h1>6.6 使用argparse进行调参<a class="headerlink" href="#argparse" title="永久链接至标题">#</a></h1>
<section id="id1">
<h2>引言<a class="headerlink" href="#id1" title="永久链接至标题">#</a></h2>
<p>在深度学习中时，超参数的修改和保存是非常重要的一步，尤其是当我们在服务器上跑我们的模型时，如何更方便的修改超参数是我们需要考虑的一个问题。这时候，要是有一个库或者函数可以解析我们输入的命令行参数再传入模型的超参数中该多好。到底有没有这样的一种方法呢？答案是肯定的，这个就是 Python 标准库的一部分：Argparse。那么下面让我们看看他是多么方便。通过本节课，您将会收获以下内容</p>
<ul class="simple">
<li><p>argparse的简介</p></li>
<li><p>argparse的使用</p></li>
<li><p>如何使用argparse修改超参数</p></li>
</ul>
</section>
<section id="id2">
<h2>6.6.1 argparse简介<a class="headerlink" href="#id2" title="永久链接至标题">#</a></h2>
<p>argsparse是python的命令行解析的标准模块，内置于python，不需要安装。这个库可以让我们直接在命令行中就可以向程序中传入参数。我们可以使用<code class="docutils literal notranslate"><span class="pre">python</span> <span class="pre">file.py</span></code>来运行python文件。而argparse的作用就是将命令行传入的其他参数进行解析、保存和使用。在使用argparse后，我们在命令行输入的参数就可以以这种形式<code class="docutils literal notranslate"><span class="pre">python</span> <span class="pre">file.py</span> <span class="pre">--lr</span> <span class="pre">1e-4</span> <span class="pre">--batch_size</span> <span class="pre">32</span></code>来完成对常见超参数的设置。</p>
</section>
<section id="id3">
<h2>6.6.2 argparse的使用<a class="headerlink" href="#id3" title="永久链接至标题">#</a></h2>
<p>总的来说，我们可以将argparse的使用归纳为以下三个步骤。</p>
<ul class="simple">
<li><p>创建<code class="docutils literal notranslate"><span class="pre">ArgumentParser()</span></code>对象</p></li>
<li><p>调用<code class="docutils literal notranslate"><span class="pre">add_argument()</span></code>方法添加参数</p></li>
<li><p>使用<code class="docutils literal notranslate"><span class="pre">parse_args()</span></code>解析参数
在接下来的内容中，我们将以实际操作来学习argparse的使用方法。</p></li>
</ul>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># demo.py</span>
<span class="kn">import</span> <span class="nn">argparse</span>

<span class="c1"># 创建ArgumentParser()对象</span>
<span class="n">parser</span> <span class="o">=</span> <span class="n">argparse</span><span class="o">.</span><span class="n">ArgumentParser</span><span class="p">()</span>

<span class="c1"># 添加参数</span>
<span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span><span class="s1">&#39;-o&#39;</span><span class="p">,</span> <span class="s1">&#39;--output&#39;</span><span class="p">,</span> <span class="n">action</span><span class="o">=</span><span class="s1">&#39;store_true&#39;</span><span class="p">,</span> 
    <span class="n">help</span><span class="o">=</span><span class="s2">&quot;shows output&quot;</span><span class="p">)</span>
<span class="c1"># action = `store_true` 会将output参数记录为True</span>
<span class="c1"># type 规定了参数的格式</span>
<span class="c1"># default 规定了默认值</span>
<span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span><span class="s1">&#39;--lr&#39;</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="nb">float</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mf">3e-5</span><span class="p">,</span> <span class="n">help</span><span class="o">=</span><span class="s1">&#39;select the learning rate, default=1e-3&#39;</span><span class="p">)</span> 

<span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span><span class="s1">&#39;--batch_size&#39;</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="nb">int</span><span class="p">,</span> <span class="n">required</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">help</span><span class="o">=</span><span class="s1">&#39;input batch size&#39;</span><span class="p">)</span>  
<span class="c1"># 使用parse_args()解析函数</span>
<span class="n">args</span> <span class="o">=</span> <span class="n">parser</span><span class="o">.</span><span class="n">parse_args</span><span class="p">()</span>

<span class="k">if</span> <span class="n">args</span><span class="o">.</span><span class="n">output</span><span class="p">:</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;This is some output&quot;</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;learning rate:</span><span class="si">{</span><span class="n">args</span><span class="o">.</span><span class="n">lr</span><span class="si">}</span><span class="s2"> &quot;</span><span class="p">)</span>

</pre></div>
</div>
<p>我们在命令行使用<code class="docutils literal notranslate"><span class="pre">python</span> <span class="pre">demo.py</span> <span class="pre">--lr</span> <span class="pre">3e-4</span> <span class="pre">--batch_size</span> <span class="pre">32</span></code>，就可以看到以下的输出</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>This is some output
learning rate: 3e-4
</pre></div>
</div>
<p>argparse的参数主要可以分为可选参数和必选参数。可选参数就跟我们的<code class="docutils literal notranslate"><span class="pre">lr</span></code>参数相类似，未输入的情况下会设置为默认值。必选参数就跟我们的<code class="docutils literal notranslate"><span class="pre">batch_size</span></code>参数相类似，当我们给参数设置<code class="docutils literal notranslate"><span class="pre">required</span> <span class="pre">=True</span></code>后，我们就必须传入该参数，否则就会报错。看到我们的输入格式后，我们可能会有这样一个疑问，我输入参数的时候不使用--可以吗？答案是肯定的，不过我们需要在设置上做出一些改变。</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># positional.py</span>
<span class="kn">import</span> <span class="nn">argparse</span>

<span class="c1"># 位置参数</span>
<span class="n">parser</span> <span class="o">=</span> <span class="n">argparse</span><span class="o">.</span><span class="n">ArgumentParser</span><span class="p">()</span>

<span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span><span class="s1">&#39;name&#39;</span><span class="p">)</span>
<span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span><span class="s1">&#39;age&#39;</span><span class="p">)</span>

<span class="n">args</span> <span class="o">=</span> <span class="n">parser</span><span class="o">.</span><span class="n">parse_args</span><span class="p">()</span>

<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;</span><span class="si">{</span><span class="n">args</span><span class="o">.</span><span class="n">name</span><span class="si">}</span><span class="s1"> is </span><span class="si">{</span><span class="n">args</span><span class="o">.</span><span class="n">age</span><span class="si">}</span><span class="s1"> years old&#39;</span><span class="p">)</span>
</pre></div>
</div>
<p>当我们不实用--后，将会严格按照参数位置进行解析。</p>
<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>$ positional_arg.py Peter <span class="m">23</span>
Peter is <span class="m">23</span> years old
</pre></div>
</div>
<p>总的来说，argparse的使用很简单，以上这些操作就可以帮助我们进行参数的修改，在下面的部分，我将会分享我是如何在模型训练中使用argparse进行超参数的修改。</p>
</section>
<section id="id4">
<h2>6.6.3 更加高效使用argparse修改超参数<a class="headerlink" href="#id4" title="永久链接至标题">#</a></h2>
<p>每个人都有着不同的超参数管理方式，在这里我将分享我使用argparse管理超参数的方式，希望可以对大家有一些借鉴意义。通常情况下，为了使代码更加简洁和模块化，我一般会将有关超参数的操作写在<code class="docutils literal notranslate"><span class="pre">config.py</span></code>，然后在<code class="docutils literal notranslate"><span class="pre">train.py</span></code>或者其他文件导入就可以。具体的<code class="docutils literal notranslate"><span class="pre">config.py</span></code>可以参考如下内容。</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">argparse</span>  
  
<span class="k">def</span> <span class="nf">get_options</span><span class="p">(</span><span class="n">parser</span><span class="o">=</span><span class="n">argparse</span><span class="o">.</span><span class="n">ArgumentParser</span><span class="p">()):</span>  
  
    <span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span><span class="s1">&#39;--workers&#39;</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="nb">int</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span>  
                        <span class="n">help</span><span class="o">=</span><span class="s1">&#39;number of data loading workers, you had better put it &#39;</span>  
                              <span class="s1">&#39;4 times of your gpu&#39;</span><span class="p">)</span>  
  
    <span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span><span class="s1">&#39;--batch_size&#39;</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="nb">int</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> <span class="n">help</span><span class="o">=</span><span class="s1">&#39;input batch size, default=64&#39;</span><span class="p">)</span>  
  
    <span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span><span class="s1">&#39;--niter&#39;</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="nb">int</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">help</span><span class="o">=</span><span class="s1">&#39;number of epochs to train for, default=10&#39;</span><span class="p">)</span>  
  
    <span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span><span class="s1">&#39;--lr&#39;</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="nb">float</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mf">3e-5</span><span class="p">,</span> <span class="n">help</span><span class="o">=</span><span class="s1">&#39;select the learning rate, default=1e-3&#39;</span><span class="p">)</span>  
  
    <span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span><span class="s1">&#39;--seed&#39;</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="nb">int</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">118</span><span class="p">,</span> <span class="n">help</span><span class="o">=</span><span class="s2">&quot;random seed&quot;</span><span class="p">)</span>  
  
    <span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span><span class="s1">&#39;--cuda&#39;</span><span class="p">,</span> <span class="n">action</span><span class="o">=</span><span class="s1">&#39;store_true&#39;</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">help</span><span class="o">=</span><span class="s1">&#39;enables cuda&#39;</span><span class="p">)</span>  
    <span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span><span class="s1">&#39;--checkpoint_path&#39;</span><span class="p">,</span><span class="nb">type</span><span class="o">=</span><span class="nb">str</span><span class="p">,</span><span class="n">default</span><span class="o">=</span><span class="s1">&#39;&#39;</span><span class="p">,</span>  
                        <span class="n">help</span><span class="o">=</span><span class="s1">&#39;Path to load a previous trained model if not empty (default empty)&#39;</span><span class="p">)</span>  
    <span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span><span class="s1">&#39;--output&#39;</span><span class="p">,</span><span class="n">action</span><span class="o">=</span><span class="s1">&#39;store_true&#39;</span><span class="p">,</span><span class="n">default</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span><span class="n">help</span><span class="o">=</span><span class="s2">&quot;shows output&quot;</span><span class="p">)</span>  
  
    <span class="n">opt</span> <span class="o">=</span> <span class="n">parser</span><span class="o">.</span><span class="n">parse_args</span><span class="p">()</span>  
  
    <span class="k">if</span> <span class="n">opt</span><span class="o">.</span><span class="n">output</span><span class="p">:</span>  
        <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;num_workers: </span><span class="si">{</span><span class="n">opt</span><span class="o">.</span><span class="n">workers</span><span class="si">}</span><span class="s1">&#39;</span><span class="p">)</span>  
        <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;batch_size: </span><span class="si">{</span><span class="n">opt</span><span class="o">.</span><span class="n">batch_size</span><span class="si">}</span><span class="s1">&#39;</span><span class="p">)</span>  
        <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;epochs (niters) : </span><span class="si">{</span><span class="n">opt</span><span class="o">.</span><span class="n">niter</span><span class="si">}</span><span class="s1">&#39;</span><span class="p">)</span>  
        <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;learning rate : </span><span class="si">{</span><span class="n">opt</span><span class="o">.</span><span class="n">lr</span><span class="si">}</span><span class="s1">&#39;</span><span class="p">)</span>  
        <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;manual_seed: </span><span class="si">{</span><span class="n">opt</span><span class="o">.</span><span class="n">seed</span><span class="si">}</span><span class="s1">&#39;</span><span class="p">)</span>  
        <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;cuda enable: </span><span class="si">{</span><span class="n">opt</span><span class="o">.</span><span class="n">cuda</span><span class="si">}</span><span class="s1">&#39;</span><span class="p">)</span>  
        <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;checkpoint_path: </span><span class="si">{</span><span class="n">opt</span><span class="o">.</span><span class="n">checkpoint_path</span><span class="si">}</span><span class="s1">&#39;</span><span class="p">)</span>  
  
    <span class="k">return</span> <span class="n">opt</span>  
  
<span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s1">&#39;__main__&#39;</span><span class="p">:</span>  
    <span class="n">opt</span> <span class="o">=</span> <span class="n">get_options</span><span class="p">()</span>
</pre></div>
</div>
<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>$ python config.py

num_workers: <span class="m">0</span>
batch_size: <span class="m">4</span>
epochs <span class="o">(</span>niters<span class="o">)</span> : <span class="m">10</span>
learning rate : 3e-05
manual_seed: <span class="m">118</span>
cuda enable: True
checkpoint_path:
</pre></div>
</div>
<p>随后在<code class="docutils literal notranslate"><span class="pre">train.py</span></code>等其他文件，我们就可以使用下面的这样的结构来调用参数。</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># 导入必要库</span>
<span class="o">...</span>
<span class="kn">import</span> <span class="nn">config</span>

<span class="n">opt</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">get_options</span><span class="p">()</span>

<span class="n">manual_seed</span> <span class="o">=</span> <span class="n">opt</span><span class="o">.</span><span class="n">seed</span>
<span class="n">num_workers</span> <span class="o">=</span> <span class="n">opt</span><span class="o">.</span><span class="n">workers</span>
<span class="n">batch_size</span> <span class="o">=</span> <span class="n">opt</span><span class="o">.</span><span class="n">batch_size</span>
<span class="n">lr</span> <span class="o">=</span> <span class="n">opt</span><span class="o">.</span><span class="n">lr</span>
<span class="n">niters</span> <span class="o">=</span> <span class="n">opt</span><span class="o">.</span><span class="n">niters</span>
<span class="n">checkpoint_path</span> <span class="o">=</span> <span class="n">opt</span><span class="o">.</span><span class="n">checkpoint_path</span>

<span class="c1"># 随机数的设置，保证复现结果</span>
<span class="k">def</span> <span class="nf">set_seed</span><span class="p">(</span><span class="n">seed</span><span class="p">):</span>
    <span class="n">torch</span><span class="o">.</span><span class="n">manual_seed</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
    <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">manual_seed_all</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
    <span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
    <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
    <span class="n">torch</span><span class="o">.</span><span class="n">backends</span><span class="o">.</span><span class="n">cudnn</span><span class="o">.</span><span class="n">benchmark</span> <span class="o">=</span> <span class="kc">False</span>
    <span class="n">torch</span><span class="o">.</span><span class="n">backends</span><span class="o">.</span><span class="n">cudnn</span><span class="o">.</span><span class="n">deterministic</span> <span class="o">=</span> <span class="kc">True</span>

<span class="o">...</span>


<span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s1">&#39;__main__&#39;</span><span class="p">:</span>
	<span class="n">set_seed</span><span class="p">(</span><span class="n">manual_seed</span><span class="p">)</span>
	<span class="k">for</span> <span class="n">epoch</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">niters</span><span class="p">):</span>
		<span class="n">train</span><span class="p">(</span><span class="n">model</span><span class="p">,</span><span class="n">lr</span><span class="p">,</span><span class="n">batch_size</span><span class="p">,</span><span class="n">num_workers</span><span class="p">,</span><span class="n">checkpoint_path</span><span class="p">)</span>
		<span class="n">val</span><span class="p">(</span><span class="n">model</span><span class="p">,</span><span class="n">lr</span><span class="p">,</span><span class="n">batch_size</span><span class="p">,</span><span class="n">num_workers</span><span class="p">,</span><span class="n">checkpoint_path</span><span class="p">)</span>

</pre></div>
</div>
</section>
<section id="id5">
<h2>总结<a class="headerlink" href="#id5" title="永久链接至标题">#</a></h2>
<p>argparse给我们提供了一种新的更加便捷的方式，在后面我们将结合其他Python标准库（pickle，json，logging）实现参数的保存和模型输出的记录。如果大家还想进一步的了解argparse的使用，大家可以点击下面提供的连接进行更深的学习和了解。</p>
<ol class="simple">
<li><p><a class="reference external" href="https://geek-docs.com/python/python-tutorial/python-argparse.html">Python argparse 教程</a></p></li>
<li><p><a class="reference external" href="https://docs.python.org/3/library/argparse.html">argparse 官方教程</a></p></li>
</ol>
</section>
</section>


              </div>
              
            </main>
            <footer class="footer-article noprint">
                
    <!-- Previous / next buttons -->
<div class='prev-next-area'>
    <a class='left-prev' id="prev-link" href="6.5%20%E6%95%B0%E6%8D%AE%E5%A2%9E%E5%BC%BA-imgaug.html" title="上一页 页">
        <i class="fas fa-angle-left"></i>
        <div class="prev-next-info">
            <p class="prev-next-subtitle">上一页</p>
            <p class="prev-next-title">6.5 数据增强-imgaug</p>
        </div>
    </a>
    <a class='right-next' id="next-link" href="PyTorch%E6%A8%A1%E5%9E%8B%E5%AE%9A%E4%B9%89%E4%B8%8E%E8%BF%9B%E9%98%B6%E8%AE%AD%E7%BB%83%E6%8A%80%E5%B7%A7.html" title="下一页 页">
    <div class="prev-next-info">
        <p class="prev-next-subtitle">下一页</p>
        <p class="prev-next-title">PyTorch模型定义与进阶训练技巧</p>
    </div>
    <i class="fas fa-angle-right"></i>
    </a>
</div>
            </footer>
        </div>
    </div>
    <div class="footer-content row">
        <footer class="col footer"><p>
  
    By ZhikangNiu<br/>
  
      &copy; Copyright 2022, ZhikangNiu.<br/>
</p>
        </footer>
    </div>
    
</div>


      </div>
    </div>
  
  <!-- Scripts loaded after <body> so the DOM is not blocked -->
  <script src="../_static/scripts/pydata-sphinx-theme.js?digest=1999514e3f237ded88cf"></script>


  </body>
</html>